WebFeature specifications

Information


Unique identifier OMICS_12673
Name WebFeature
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 3.1
Stability No
Maintained No

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Information


Unique identifier OMICS_12673
Name WebFeature
Interface Web user interface
Restrictions to use None
Input format pdb, Protein Data Bank ID
Computer skills Basic
Version 4.0
Stability No
Maintained No

Maintainer


This tool is not available anymore.

Publication for WebFeature

WebFeature in publications

 (3)
PMCID: 4179157
PMID: 25229188
DOI: 10.3390/toxins6092719

[…] suggestion that it is important for the stability of this protease []. notably, the investigation of potential calcium-binding sites within the crystal structure of esppα (pdb: 3sze) [] using the webfeature program [] indicated that ca2+ binding might occur at the interfacing α-helical region connecting the proteolytic domain1 and the β-helical backbone as well as in loop 165 (data […]

PMCID: 2808310
PMID: 20003365
DOI: 10.1186/1472-6807-9-72

[…] calcium-binding sites were predicted using feature. a complete description of feature can be found in the original paper and a web server of feature is also provided in http://feature.stanford.edu/webfeature[]. in summary, we make observations of 66 physical-chemical properties on a dataset of experimentally determined structures containing calcium-binding sites. we then compile a conditional […]

PMCID: 1435900
PMID: 16526955
DOI: 10.1186/1472-6807-6-4

[…] []. profunc uses sequence, structure and residue templates to characterize proteins of interest []. proknow is a resource for annotating go terms using bayes' theorem and protein structure []. webfeature uses supervised learning to train models of protein environments for inferring functional sites in protein structures []., here, we have integrated s-blest, psi-blast and hmmer to report […]


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WebFeature institution(s)
Department of Computer Science, San Francisco State University, San Francisco, CA, USA; Center for Computing for Life Sciences, San Francisco State University, San Francisco, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA
WebFeature funding source(s)
Supported by an Amazon Web Services in Education Research Grant to Center for Computing for Life Sciences at San Francisco State University, awarded June 18, 2012; by NIH grants LM05652, GM072970, GM102365 and the NSFBIOX2 award CNS-0619926.

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